The increasingly widespread use of social software (e.g., Wikis, Google Docs) in second language (L2) settings has brought a renewed attention to collaborative writing. Although the current methodological approaches to examining collaborative writing are valuable to understand L2 students' interactional patterns or perceived experiences, they can be insufficient to capture the quantity and quality of writing in networked online environments. Recently, the evolution of techniques for analyzing big data has transformed many areas of life, from information search to marketing. However, the use of data and text mining for understanding writing processes in language learning contexts is largely underexplored. In this article, we synthesize the current methodological approaches to researching collaborative writing and discuss how new text mining tools can enhance research capacity. These advanced methods can help researchers to elucidate collaboration processes by analyzing user behaviors (e.g., amount of editing, participation equality) and their link to writing outcomes across large numbers of exemplars. We introduce key research examples to illustrate this potential and discuss the implications of integrating the tools for L2 collaborative writing research and pedagogy.